The Agile Embedded Podcast

We talk with Tobias Kästner, a physicist-turned-software-architect and technical consultant at Inovex, about his journey from painfully slow hardware-software integration cycles to achieving three-week hardware sprints. Tobias shares hard-won lessons from medical device development, where fuzzy requirements and constant feedback from life scientists forced his team to rethink traditional approaches. The conversation centers on practical techniques: breaking monolithic PCB designs into modular "feature boards" connected via shields (think Arduino-style), using Git for hardware version control with SHA-1s printed on silkscreens, and leveraging tools like Zephyr RTOS to enable plug-and-play firmware that matches the modularity of the hardware. Tobias explains how relaxing constraints like board size and using automation to merge schematics allowed his team to iterate rapidly while maintaining a clear path to final form-factor designs. We discuss how this approach scaled to projects with 120+ people across multiple teams, and why the interplay between system architecture, organizational structure, and information flow matters more than most realize. Key Topics [02:30] The painful reality of traditional hardware development: six-month wait for hardware, nine months of debugging [08:00] Breaking apart monolithic PCB designs into modular feature boards with shield connectors [12:45] Relaxing constraints: larger board areas, autorouting, and prioritizing testability over final form factor [18:20] Version control for hardware: putting schematics in Git and printing SHA-1s on silkscreens [22:00] Using automation to merge feature board schematics into final form-factor designs [26:15] Firmware architecture: NuttX, Zephyr, KConfig, and device trees for modular, plug-and-play software [35:40] Scaling agile hardware-software co-development to 120+ person projects across multiple teams [39:00] The interplay of system architecture, organizational architecture, and information architecture Notable Quotes "When the board arrived, not a single line of code had been written for it because no one had been able to touch it. It took us nine additional months to debug all the things out of it." — Tobias Kästner "I've never seen any board working the first time. I've never seen any prototype without thin wires patching things out, but that's maybe a different story." — Tobias Kästner "We cannot think these architectures as independent of one another. If we have limitations in two of these architectures, we will see these limitations in the third architecture as well." — Tobias Kästner Resources Mentioned Inovex - Tobias's company offering engineering consulting services, trainings, and expertise in embedded systems, IoT, and full-stack development Zephyr RTOS - Open-source real-time operating system with KConfig, device tree support, and extensive driver library that Tobias recommends for modular firmware development NuttX RTOS - Apache Foundation RTOS with clean device driver model and KConfig support that Tobias used in earlier projects KiCad - Open-source PCB design software with emerging Python API support for schematic automation Services and Contact Through Inovex, Tobias provides trainings for both Zephyr and Yocto Linux, as well as consultancy and engineering support for embedded projects -- from 1-2 day workshops evaluating architectural state and cost/benefit analysis, to first prototypes, to full-fledged software development. With partners such as alpha-board (Berlin) and Blunk electronic (Erfurt), they also offer agile hardware services and help teams get started with the methods discussed in this episode. Email: [email protected] Tobias Kästner on LinkedIn tobiaskaestner on the Zephyr Discord Channel Links Companies: Inovex -- Embedded Systems Blunk electronic alpha-board Navimatix Talks and publications: Modular and Agile HW Development (2018 talk) Leveraging Zephyr's HW Abstraction for Agile Systems Engineering (2023 talk) Whitepaper: Agile in der Hardware -- by Gregor Gross, Christoph Schmiedinger, and Tobias Kästner Leveraging Zephyr for Functional Architecture Decomposition (2025 talk) Books recommended by Tobias: Small Groups as Complex Systems -- Holly Arrow et al., SAGE Publications The Dao of Complexity -- Jean Boulton, DeGruyter You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/  

We explore how test-driven development (TDD) remains essential—perhaps more than ever—when working with AI coding tools. Luca shares his evolved workflow using Claude Code, breaking down how he structures tests in three phases: test ideas, test outlines, and test implementations. We discuss why TDD provides the necessary control and confidence when AI generates code, how it prevents technical debt accumulation, and why tests serve as precise specifications for AI rather than afterthoughts. The conversation covers practical challenges like AI's tendency toward "success theater" (overly generous assertions), the importance of maintaining tight control over code quality, and why the bottleneck in AI-assisted development isn't code generation—it's expressing clear intent. We also touch on code spikes, large-scale refactorings, and why treating AI development as pair programming keeps you in the driver's seat. If you're wondering whether TDD still matters when AI writes your code, this episode makes a compelling case that it matters more than ever. Key Topics [02:30] Why TDD still matters with AI: confidence and control over generated code [06:45] Tests as specifications: describing desired behavior to AI rather than writing prompts [09:20] The three-phase test workflow: test ideas, test outlines, and implementations [15:30] Pair programming with AI: staying at the conceptual level while AI handles implementation [20:15] Code spikes and exploration: using AI to answer questions before writing production tests [24:40] AI failure modes: over-mocking and "success theater" with weak assertions [28:50] Large-scale refactorings: how AI excels at updating hundreds of tests simultaneously [32:10] The real bottleneck: expressing intent and specifications, not code generation speed Notable Quotes "As far as I am concerned, test-driven development is just about writing prompts for the AI that it can then use to build what you want it to build." — Luca "If you expect that a five-line prompt resulting in 10,000 lines of code will not result in 9,995 lines of uncertainty, you're just deluding yourself." — Luca "You can be five times faster than you were before and still maintain a very high production level quality code, but you probably can't be a hundred times faster." — Jeff Resources Mentioned Claude Code - Terminal-based AI coding assistant that Luca uses for TDD workflows, keeping conceptual work separate from code-level work Embedded AI Podcast - Luca's separate podcast focusing on AI in embedded systems, co-hosted with Ryan Torvik Luca's AI Training Courses - Hands-on trainings for using AI in embedded systems development (and much more!) links to all of Luca's work - Training, consulting, podcasts, conference talks and everything else You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/  

In this second part of our series on engineering organizations, Jeff and Luca explore how companies that build products should focus their efforts differently depending on their stage and scope. We start with startups and early-stage companies desperately searching for product-market fit, where the brutal truth is: quality doesn't matter yet. Your MVP should embarrass you—if it doesn't, you waited too long. We discuss the critical mental shift from throwaway prototypes to proper engineering once validation arrives, and why technical founders often fail by solving the wrong problem brilliantly. Moving up the ladder, we examine narrow-focus companies that have found their niche—like the German firm that does nothing but maintain a 100-year-old anchor chain machine, or specialists in medium-power electrical switches. These companies win through efficiency and deep expertise, but face existential risk if the market shifts. Finally, we tackle wide-focus companies introducing multiple product lines, where the challenge becomes running internal startups while managing established products, each requiring radically different approaches. The key insight: your focus must match your product's lifecycle stage, whether that's ruthless speed, cost optimization, or high-level process learning. Key Topics [02:30] Startups and early-stage companies: the existential search for product-market fit [06:45] The MVP philosophy: if you're not embarrassed, you waited too long [11:20] Quality vs. speed vs. scope: why quality doesn't matter in early stages [15:40] The Potemkin village approach: building facades to validate demand [19:15] Embedded products and MVPs: when physical products need creative shortcuts [23:50] The critical switch: from prototypes to proper engineering after validation [28:30] Narrow-focus companies: German hidden champions and deep specialization [34:10] Wide-focus companies: running internal startups within established organizations [40:25] Product teams and parallel focuses: managing different lifecycle stages simultaneously [45:00] Large established companies: high-level process learning and avoiding organizational weight Notable Quotes "If you read the Lean Startup, they will explicitly say: if you weren't embarrassed by your MVP, you waited too long. It really has to be painfully flimsy because you cannot afford to do it well." — Luca "Quality doesn't even factor because you're very explicitly building mock-ups from chewing gum and paper mache. They are fully intended to be thrown away." — Luca "Getting that product-market fit is existential. You will die if you do not get it and get it relatively quickly." — Jeff Resources Mentioned The Lean Startup - Eric Ries' book discussing MVP philosophy and the importance of being embarrassed by your first product The Mom Test - Rob Fitzpatrick's book about getting real customer feedback and validation through financial commitment The Art of Innovation - Tom Kelley's book on IDEO's design process, including the clothespin switch story Luca's Website - Trainings on embedded agile, AI in embedded systems, and more Jeff's Website - Consulting services for medical device software development You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/  

In this first part of a two-part series, Jeff and Luca explore how different types of service-oriented engineering organizations should focus their learning and improvement efforts. Drawing from their consulting experience, they examine three distinct categories: product development firms that turn client ideas into reality, engineering development firms that sell specialized technical expertise, and solo engineers who package all necessary knowledge into one person.The core insight: what you should focus on learning depends entirely on what you're actually selling. Product development firms need to master the entire client journey and product design process, not just engineering excellence. Engineering development firms must become technical wizards in a specific domain that clients actually value. Solo engineers face the challenge of needing deep expertise while wearing every business hat. Across all three types, the common traps are the same: focusing too much on craft and too little on client experience, failing to specialize, and not investing enough in teaching as marketing.Throughout the discussion, Jeff and Luca emphasize that for service firms, you are the product - and that changes everything about where you should direct your improvement efforts. The conversation is grounded in real experiences, including some cautionary tales about firms that tried to be everything to everyone.Key Topics[00:00] Introduction: Two-part series on engineering organizations and their different focuses[02:30] Overview of the framework: Service firms vs. product-building companies[05:15] Product development firms: Why engineering excellence isn't enough[08:45] The critical importance of product design and client guidance over pure engineering[12:20] Process-level learning: Shortening cycle times and enabling rapid prototyping[15:40] The Irinos example: In-house board manufacturing to tighten feedback loops[18:30] Requirements will always change - designing for learning, not perfection[21:00] The danger of being a generalist: Why specialization matters for service firms[24:15] Engineering development firms: Selling technical expertise, not complete products[27:45] Technology-focused learning: Going deep on specific technical capabilities[30:20] The trap of becoming a commodity: Why domain expertise beats technology alone[33:40] The forklift invoice review example: You can't specialize too narrowly[35:30] Solo engineers: The complete package vs. temporary employee trap[39:00] Common failures across all service firms: Too much craft focus, too little client experience and marketing[41:30] Teaching as the best form of marketing for technical service firmsNotable Quotes"The customers don't actually hire them for their engineering skills. They are sort of a given. But what such a product development firm should offer the client is guiding them through the development process, which they don't have enough skills for to do it on their own." — Luca"Engineering is not the point. The unit of work is delivering a working product to the client that satisfies their business case, that has a reasonable cost to manufacture, and that you feel confident your own client has validated their market." — Jeff"It's not that engineering is irrelevant, but rather that it's table stakes. This is just taken for granted, but what such a product development firm should offer is guiding them through the development process." — Luca"You almost can't be narrow enough. I remember our friend Philip Morgan having this example of a company that specializes in reviewing invoices of forklift repairs. This is what they do. They review forklift repair invoices. And they're doing very well apparently." — Luca"Teaching and giving information and solving problems publicly is the best form of marketing. It's not advertising. It's building trust with an audience." — JeffResources MentionedIDEO - Prototypical design firm mentioned as an example of companies specializing in product designIRNAS - Product development firm with in-house board manufacturing capabilities, featured in previous episodes, exemplifying tight feedback loopsPhilip Morgan - Consultant and friend mentioned for his example about specialization (forklift invoice review company)Jeff Gable's website - Jeff's consulting services for medical device software development and advisoryLuca Ingianni's website - Luca's training products and resources for embedded systems, IoT, and AIConnect With UsStay tuned for Part 2, where we'll explore organizations that build products and what they should focus on when the market decidesIf you're in the medical device industry and need help with embedded software - either writing it or navigating the regulatory landscape - reach out to Jeff at jeffgable.comCheck out Luca's training products for embedded systems, IoT, and AI at luca.engineerReflect on your own organization: Are you focusing on the right things for the type of service firm you are? Are you specializing e

In this episode, we sit down with Milica Kostic, an embedded software architect from Belgrade, Serbia, to discuss her journey from C/C++ to Rust and what it means for embedded development. Milica shares her experience adopting Rust in production environments, starting with an embedded Linux project using a microservice architecture that allowed for clean isolation of Rust code.We explore the practical realities of learning Rust as an experienced C/C++ developer - yes, there's a learning curve, and yes, the compiler will slap you on the wrist frequently. But Milica explains how the development experience, with cargo as a package manager and built-in tooling for testing and static analysis, makes the journey worthwhile. She's candid about where Rust shines (embedded Linux, greenfield projects) and where challenges remain (microcontroller support, IDE tooling, vendor backing).The conversation touches on the bigger question facing our industry: with memory safety becoming critical in our connected world, what role should Rust play in new embedded projects? While Milica takes a measured stance - acknowledging that C and C++ aren't going anywhere - she's clearly excited about Rust's potential, especially in safety-critical domains like medical devices. Whether you're Rust-curious or still skeptical, this episode offers a grounded perspective from someone who's actually shipped production code in Rust.Key Topics[02:30] Milica's background in embedded systems and her journey from electrical engineering to embedded software development, with focus on safety-critical industries like medical devices[04:15] The path to adopting Rust: from first hearing about it in 2020 to finding a client project willing to embrace it, and the importance of having experienced Rust developers on the team[07:00] Choosing the right project for Rust adoption: embedded Linux with microservice architecture as an ideal starting point, avoiding complex C/C++ interoperability[10:45] The learning curve: getting used to the Rust compiler's strictness, discovering the ecosystem of unofficial but widely-used crates, and how learning Rust improved C++ skills[14:20] What makes Rust development pleasant: cargo as package manager, built-in testing and static analysis, cleaner code organization with modules, and writing unit tests alongside source code[17:30] Current limitations: lack of official vendor support for microcontrollers, community-driven development, potential gaps in certified stacks (like BLE), and IDE support challenges[20:15] Interfacing Rust with C and C++: C binding works well, C++ has limitations with inheritance and templates, and the safety considerations when using unsafe code blocks[25:40] Integrating Rust into legacy projects: when it makes sense (isolated new features requiring memory safety) and when it doesn't (just for experimentation), plus maintenance considerations[30:00] The big question: Is it irresponsible not to use Rust for new projects? Discussion of Philip Marcraff's strong stance and Milica's more nuanced view considering team knowledge, existing tooling, and project context[33:45] The influence between languages: how C++ is learning from Rust's memory safety features, and why the borrow checker is harder to retrofit than basic safety improvements[36:20] Rust in operating systems: adoption in the Linux kernel and Microsoft Windows, and major tech companies pushing C++/Rust interoperability forward[39:00] The future of Rust in embedded: Milica's view that C, C++, and Rust will coexist, each with their own use cases, advantages, and trade-offsNotable Quotes"Learning Rust has also made me a better C++ developer as well. Once you get used to those rules, you apply them in C++ as well." — Milica"Just like writing Rust code is pleasant. It flows much nicer than or easier than it would with C++, for example. The way you organize your code, in my opinion, is also cleaner." — Milica"If you are developing Rust for embedded systems on microcontrollers, you need to be aware that there is no official vendor support. Everything currently is open source and driven by the community." — Milica"You definitely do not lose benefits of using Rust for the rest of your codebase when using a C library. That C library is isolated, and if there are some memory issues, then you know where to look." — Milica"I think most of the benefits come from starting with Rust in the first place. So having a clean slate, starting a new product, new project with Rust. That's where you see the most benefits." — MilicaResources MentionedEmbassy - An async framework used in embedded Rust projects, mentioned as a good starting point for greenfield embedded developmentZephyr RTOS - Real-time operating system that is working on official Rust integration, though not fully there yetRust Rover - JetBrains' official IDE for Rust development, released about a year and a half ago, though with some limitations for embedded developmentZed - A new IDE written completely

We talk with Matt Trentini, Principal Software Engineer at Planet Innovation, about using MicroPython for professional embedded development—including medical devices. Matt shares how he was drawn back to embedded development after becoming jaded with traditional C-based workflows, and explains why MicroPython's interactive REPL and rapid development cycle have become game-changers for his team.We explore the practical realities of using an interpreted language on microcontrollers: how Planet Innovation uses it for Class B medical devices, what the performance trade-offs actually look like, and how features like the Unix port enable robust testing. Matt walks us through deployment considerations, explains how to integrate C code when needed, and shares compelling stories about real-time client demos that would be impossible in C++.Whether you're skeptical about high-level languages in embedded systems or curious about alternatives to traditional development workflows, this conversation offers a grounded, engineering-focused look at what MicroPython can—and can't—do in production environments.Key Topics[03:30] Matt's background and why he left embedded development before MicroPython brought him back[08:45] What MicroPython is: a complete re-implementation of Python for microcontrollers with REPL, filesystem, and machine module[13:20] How Planet Innovation introduced MicroPython through an OpenMV vision processing project[17:15] The game-changing power of the REPL for interactive hardware development and testing[21:40] Running MicroPython code on x86 for testing, and the mock machine library approach[26:30] Python library compatibility: what works, what doesn't, and memory considerations[29:50] Integrating C and C++ code through extension modules for performance-critical sections[33:10] Performance realities: 10-100x slower in interpreter, but can always drop to C speed when needed[37:45] Tooling: MPRemote, the magical mount feature, and development workflow[42:20] When NOT to use MicroPython: cost-sensitive high-volume products and resource constraints[45:30] Using MicroPython in Class B medical devices and safety-critical applications[49:15] Garbage collection: simple, predictable, and controllable—can be disabled when needed[52:40] Real-time client demo story: modifying state machines during a call and showing results immediately[56:20] Deployment: frozen code, disabling REPL and filesystem, and OTA considerations[01:01:30] Common mistakes: logic errors and inadvertent allocations rather than memory corruption[01:05:45] Threading, AsyncIO, and the Global Interpreter Lock across different ports[01:08:20] State machine frameworks: StateChart, Yasme, and PyTransitions[01:11:40] Junior developer productivity: faster onboarding compared to C/C++ embedded development[01:15:10] Getting started: board bring-up as an ideal first use case for MicroPython[01:17:50] Hardware-in-the-loop testing as a low-risk way to try MicroPythonNotable Quotes"It's hard to overstate how game changing the REPL is. Particularly as an embedded engineer, once you see that you can interactively talk to a peripheral, you can generate your own I2C, squirt it across and see what the peripheral does with it—suddenly driver development has just become easy to experiment with." — Matt Trentini"My trite answer is that MicroPython is slow—10 to 100 times slower than C in the interpreter. But my flip side answer is that it can always be made as fast as C because you can always drop into C to write things." — Matt Trentini"There was a moment in a recent project where we were discussing the workflow of a state machine with the client, and while we were on a call, another engineer was actually making changes to MicroPython code. Literally a couple minutes after we'd been hashing out the details, they showed the changes in the state machine using the REPL. The client was blown away—in 25 years of development, I have never had that kind of turnaround in C and C++." — Matt Trentini"If you want to make a good friend of your electronics engineers, give them a build of MicroPython that can run on their custom board. In the past, they would typically be waiting for weeks or sometimes months before a software resource could be assigned. Now I can turn around a MicroPython build in a day or two, and they can test I2C, GPIOs, and UARTs themselves." — Matt Trentini"The irony is that the people who have embedded C knowledge are actually the people that can benefit the most from MicroPython. It's like having a superpower—you understand what MicroPython is doing in the background, you know you're just effectively writing a lot less code." — Matt TrentiniResources MentionedMicroPython Official Site - The official MicroPython project website with documentation and downloadsOpenMV - Computer vision project using MicroPython for camera-based applicationsMPRemote - Tool for interacting with MicroPython devices, including the magical mount featurePlanet Innovation - Medi

In this episode, Jeff and Luca tackle the unique challenges faced by solo embedded developers. Drawing from their own experiences as consultants, they explore why working alone makes it harder to maintain good development practices - from the constant pressure to multitask across different stakeholder demands, to the difficulty of wearing multiple hats as leader, manager, and contributor simultaneously.The conversation moves through common pitfalls: skipping documentation because "it's all in my head," letting code reviews slide, making questionable architecture decisions without a sounding board, and neglecting tools like simulators under time pressure.But this isn't just a catalog of problems - Jeff and Luca share practical strategies for staying disciplined, from creating mastermind groups with fellow solo developers to strategically hiring third-party reviewers for architecture decisions. They discuss how to push back on arbitrary deadlines, the value of enforcing process on yourself, and why sometimes the best productivity hack is spending money on training to force yourself to sharpen your skills.Whether you're a solo consultant, the only developer at a startup, or part of a small team, this episode offers honest insights into maintaining quality and sanity when you're working largely on your own.Key Topics[00:00] Introduction: Can you do agile as a solo developer?[03:30] First principles of agile development and why they work for solo developers[06:15] Unique difficulties: Making progress in only one area at a time[10:45] Wearing three hats: Being leader, manager, and contributor simultaneously[15:20] Budget pressure and the challenge of 'nice to haves' that actually matter[22:30] The importance of delivering something palpable after the first sprint[28:00] Bad habit #1: No documentation because 'it's all in my head'[35:45] Bad habit #2: No code reviews and potential solutions[40:15] Using LLMs for code review: What works and what doesn't[44:30] Bad habit #3: Idiosyncratic or terrible code architecture[50:00] Bad habit #4: Not making it easy for other developers to take over[53:20] Bad habit #5: Neglecting simulators and development board support[57:00] Breaking bad habits: Working solo together through mastermind groups[62:30] Enforcing process on yourself and recognizing arbitrary deadlines[67:45] Applying agility to agility: Inspecting and adapting your own process[71:00] Sharpening the axe: Jeff's experience with the Embedded SummitNotable Quotes"When you're a solo developer, you have to be the leader, the manager, and the contributor for the software effort. Those are different roles and different skills." — Jeff"You must apply agility to agility. Inspect your process, figure out what works, what doesn't work. If something is annoying to you, either it's pointing you towards a real deficiency or it's just objectively a terrible process and you should change it." — Luca"It's really scary how effective rubber duck debugging is. You start to think of what the other person would answer, even though you're just talking to a rubber duck." — Jeff"Simple and easy are not the same things. Having good development practices, just like losing weight, is simple. It's just not easy." — Jeff"Dear listeners, have you ever paid with your own money for software development? Because I have. And it's really unnerving. You tell this developer to go do something and they just sort of disappear and you can hear the meter running." — LucaResources MentionedQP Real-Time Framework - Event-driven framework by Miro Samek for embedded systems, mentioned as a game-changing architecture choice for medical device development with active object patterns and hierarchical state machinesZephyr RTOS - Open-source real-time operating system for embedded devices, discussed as an important technology for solo developers to master for modern IoT and connected device projectsEmbedded Online Conference / Embedded Summit - Premier embedded systems conference offering both online and in-person training, including hands-on bootcamps for technologies like Zephyr RTOS, organized by Jacob Beningo and Stephane BoucherAgile Embedded Academy - Luca's newly launched training platform focused on applying agile methodologies specifically to embedded systems development, offering practical courses for embedded teamsFDA Software Documentation Requirements - Regulatory documentation standards for medical device software including requirements specifications, architecture documents, detailed design, and test protocols required for FDA submissionsMob Programming Methodology - Collaborative development approach where entire team works on single task together, referenced as an alternative to traditional multitasking, promoted by Austin Chadwick and Chris You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agilee

In this fascinating episode, we dive deep into the world of agile hardware development with Gregor Gross, a civil engineer who runs Alpha-board, a PCB design service company in Berlin, Germany. Gregor shares his unique perspective on applying agile principles to hardware projects, where you can't just hit compile and get a new increment.We explore the practical challenges of agile hardware development, from structuring contracts differently to breaking complex PCBs into testable modules and shields. Gregor discusses the importance of mixed hardware-software teams, the role of automated documentation, and why his engineers resist pair programming despite its proven benefits. The conversation also touches on the cultural barriers to adopting agile practices in traditional hardware companies and the innovative approaches needed to make agile hardware development work in a service provider context.Key Topics[02:30] Introduction to Alpha-board and agile hardware development services[05:15] Defining agile principles: functionality-focused development and prioritization[12:45] Contract challenges: moving from fixed-price to hourly service contracts[18:20] Practical agile hardware: breaking PCBs into testable modules and shields[25:10] Mixed teams and automated documentation for hardware-software collaboration[32:40] The pair programming experiment: better results but team resistance[38:55] Customer expectations and the need for end-user access in agile projects[44:30] Version control and Git integration for hardware design workflowsNotable Quotes"We are probably the only service provider in Germany that offers agile hardware development because I don't see so many people speaking about it." — Gregor Gross"Software is soft, hardware is hard. I was waiting to say that." — Gregor Gross"My experience from pairing was they work harder. They feel like they observe themselves... but there wasn't any mistakes. And actually they themselves said they were surprised by how much they did because they did more than twice what they expected." — Gregor Gross"It's better to have different shields and modules that have some of the functionality. And so you can start iterating through these functionalities and test them." — Gregor GrossResources MentionedAlpha-board - Gregor's PCB design and agile hardware development service companyZephyr OS - Real-time operating system mentioned for prototyping with sample boardsKiCad - Open source EDA tool recommended for mixed teams and transparencyAndrew Greenberg's KiCon Presentation - Presentation on schematic style guides for better readability You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/  

In this special crossover episode with the brand-new Embedded AI Podcast, Luca and Jeff are joined by Ryan Torvik, Luca's co-host on the Embedded AI podcast, to explore the intersection of AI-powered development tools and agile embedded systems engineering. The hosts discuss practical strategies for using Large Language Models (LLMs) effectively in embedded development workflows, covering topics like context management, test-driven development with AI, and maintaining code quality standards in safety-critical systems. The conversation addresses common anti-patterns that developers encounter when first adopting LLM-assisted coding, such as "vibe coding" yourself off a cliff by letting the AI generate too much code at once, losing control of architectural decisions, and failing to maintain proper test coverage. The hosts emphasize that while LLMs can dramatically accelerate prototyping and reduce boilerplate coding, they require even more rigorous engineering discipline - not less. They discuss how traditional agile practices like small commits, continuous integration, test-driven development, and frequent context resets become even more critical when working with AI tools. For embedded systems engineers working in safety-critical domains like medical devices, automotive, and aerospace, the episode provides valuable guidance on integrating AI tools while maintaining deterministic quality processes. The hosts stress that LLMs should augment, not replace, static analysis tools and human code reviews, and that developers remain fully responsible for AI-generated code. Whether you're just starting with AI-assisted development or looking to refine your approach, this episode offers actionable insights for leveraging LLMs effectively while keeping the reins firmly in hand. ## Key Topics * [03:45] LLM Interface Options: Web, CLI, and IDE Plugins - Choosing the Right Tool for Your Workflow* [08:30] Prompt Engineering Fundamentals: Being Specific and Iterative with LLMs* [12:15] Building Effective Base Prompts: Learning from Experience vs. Starting from Templates* [16:40] Context Window Management: Avoiding Information Overload and Hallucinations* [22:10] Understanding LLM Context: Files, Prompts, and Conversation History* [26:50] The Nature of Hallucinations: Why LLMs Always Generate, Never Judge* [29:20] Test-Driven Development with AI: More Critical Than Ever* [35:45] Avoiding 'Vibe Coding' Disasters: The Importance of Small, Testable Increments* [42:30] Requirements Engineering in the AI Era: Becoming More Specific About What You Want* [48:15] Extreme Programming Principles Applied to LLM Development: Small Steps and Frequent Commits* [52:40] Context Reset Strategies: When and How to Start Fresh Sessions* [56:20] The V-Model Approach: Breaking Down Problems into Manageable LLM-Sized Chunks* [01:01:10] AI in Safety-Critical Systems: Augmenting, Not Replacing, Deterministic Tools* [01:06:45] Code Review in the AI Age: Maintaining Standards Despite Faster Iteration* [01:12:30] Prototyping vs. Production Code: The Superpower and the Danger* [01:16:50] Shifting Left with AI: Empowering Product Owners and Accelerating Feedback Loops* [01:19:40] Bootstrapping New Technologies: From Zero to One in Minutes Instead of Weeks* [01:23:15] Advice for Junior Engineers: Building Intuition in the Age of AI-Assisted Development ## Notable Quotes > "All of us are new to this experience. Nobody went to school back in the 80s and has been doing this for 40 years. We're all just running around, bumping into things and seeing what works for us." — Ryan Torvik > "An LLM is just a token generator. You stick an input in, and it returns an output, and it has no way of judging whether this is correct or valid or useful. It's just whatever it generated. So it's up to you to give it input data that will very likely result in useful output data." — Luca Ingianni > "Tests tell you how this is supposed to work. You can have it write the test first and then evaluate the test. Using tests helps communicate - just like you would to another person - no, it needs to function like this, it needs to have this functionality and behave in this way." — Ryan Torvik > "I find myself being even more aggressively biased towards test-driven development. While I'm reasonably lenient about the code that the LLM writes, I am very pedantic about the tests that I'm using. I will very thoroughly review them and really tweak them until they have the level of detail that I'm interested in." — Luca Ingianni > "It's really forcing me to be a better engineer by using the LLM. You have to go and do that system level understanding of the problem space before you actually ask the LLM to do something. This is what responsible people have been saying - this is how you do engineering." — Ryan Torvik > "I can use LLMs to jumpstart me or bootstrap me from zero to one. Once there's something on the screen that kind of works, I can usually then apply my general programming skill, m

In this episode, Jeff interviews Luca about his intensive experience presenting at five conferences in two and a half days, including the Embedded Online Conference and a German conference where he delivered a keynote on AI-enhanced software development. Luca shares practical insights from running an LLM-only hackathon where participants were prohibited from manually writing any code that entered version control—forcing them to rely entirely on AI tools.The conversation explores technical challenges in AI-assisted embedded development, particularly the importance of context management when working with LLMs. Luca reveals that effective AI-assisted coding requires treating prompts like code itself—version controlling them, refining them iteratively, and building project-specific prompt libraries. He discusses the economics of LLM-based development (approximately one cent per line of code), the dramatic tightening of feedback loops from days to minutes, and how this fundamentally changes agile workflows for embedded teams.The episode concludes with a discussion about the evolving role of embedded developers—from code writers to AI supervisors and eventually to product owners with deep technical skills. Luca and Jeff address concerns about maintaining core software engineering competencies while embracing these powerful new tools, emphasizing that understanding the craft remains essential even as the tools evolve.Key Topics[02:15] LLM-only hackathon constraints: No human-written code in version control[04:30] Context management as the critical skill for effective LLM-assisted development[08:45] Explicit context control: Files, directories, API documentation, and web content integration[11:20] LLM hallucinations: When AI invents file contents and generates diffs against phantom code[13:00] Economics of AI-assisted coding: Approximately $0.01 per line of code[15:30] Tightening feedback loops: From day-long iterations to minutes in agile embedded workflows[17:45] Rapid technical debt accumulation: How LLMs can create problems faster than humans notice[19:30] The essential role of comprehensive testing in AI-assisted development workflows[22:00] Challenges with TDD and LLMs: Getting AI to take small steps and wait for feedback[26:15] Treating prompts like code: Version control, libraries, and project-specific prompt management[29:40] External context management: Coding style guides, plan files, and todo.txt workflows[32:00] LLM attention patterns: Beginning and end of context receive more focus than middle content[34:30] The evolving developer role: From coder to prompt engineer to AI supervisor to technical product owner[38:00] Code wireframing: Rapid prototyping for embedded systems using AI-generated implementations[40:15] Maintaining software engineering skills in the age of AI: The importance of manual practice[43:00] Software engineering vs. software carpentry: Architecture and goals over syntax and implementationNotable Quotes"One of the hardest things to get an LLM to do is nothing. Sometimes I just want to brainstorm with it and say, let's look at the code base, let's figure out how we're going to tackle this next piece of functionality. And then it says, 'Yeah, I think we should do it like this. You know what? I'm going to do it right now.' And it's so terrible. Stop. You didn't even wait for me to weigh in." — Luca Ingianni"LLMs making everything faster also means they can create technical debt at a spectacular rate. And it gets a little worse because if you're not paying close attention and if you're not disciplined, then it kind of passes you by at first. It generates code and the code kind of looks fine. And you say, yeah, let's keep going. And then you notice that actually it's quite terrible." — Luca Ingianni"I would not trust myself to review an LLM's code and be able to spot all of the little subtleties that it gets wrong. But if I at least have tests that express my goals and maybe also my worries in terms of robustness, then I can feel a lot safer to iterate very quickly within those guardrails." — Luca Ingianni"Roughly speaking, the way I was using the tool, I was spending about a cent per line. Which is about two orders of magnitude below what a human programmer roughly costs. It really is a fraction. So that's nice because it makes certain things approachable. It changes certain build versus buy decisions." — Luca Ingianni"You can tighten your feedback loops to an absurd degree. Maybe before, if you had a really tight feedback loop between a product owner and a developer, it was maybe a day long. And now it can be minutes or quarters of an hour. It is so much faster. And that's not just a quantitative step. It's also a qualitative step." — Luca Ingianni"Some of my best performing prompts came from a place of desperation where one of my prompts is literally 'wait wait wait you didn't do what we agreed you would do you did not read the files carefully.' And I'd like to use this prompt now, eve

In this comprehensive episode, Luka Mustafa, founder and CEO of Irnas Product Development, provides an in-depth exploration of Zephyr RTOS and its transformative impact on embedded development. We dive deep into how Zephyr's Linux Foundation-backed ecosystem enables hardware-agnostic development, dramatically reducing the time spent on foundational code versus business-value features. Luka shares practical insights from five years of specializing in Zephyr development, demonstrating how projects can achieve remarkable portability - including running the same Bluetooth code on different chip architectures in just an hour, and even executing embedded applications natively on Linux for development purposes.The discussion covers Zephyr's comprehensive testing framework (Twister), CI/CD integration capabilities, and the cultural shift required when moving from traditional bare-metal development to this modern RTOS approach. We explore real-world applications from low-power IoT devices consuming just 5 microamps to complex multi-core systems, while addressing the learning curve challenges and when Zephyr might not be the right choice. This episode is essential listening for embedded teams considering modernizing their development practices and leveraging community-driven software ecosystems.Key Topics[03:15] Zephyr RTOS fundamentals and Linux Foundation ecosystem benefits[08:30] Hardware abstraction and device tree implementation for portable embedded code[12:45] Nordic Semiconductor strategic partnership and silicon vendor support landscape[18:20] Native POSIX development capabilities and cross-platform debugging strategies[25:10] Learning curve challenges: EE vs CS background adaptation to Zephyr development[32:40] Resource requirements and low-power implementation on constrained microcontrollers[38:15] Multi-vendor chip support: STMicroelectronics, NXP, and industry adoption trends[42:30] Safety-critical applications and ongoing certification processes[45:50] Organizational transformation strategies and cultural adaptation challenges[52:20] Zbus inter-process communication and modular development architecture[58:45] Twister testing framework and comprehensive CI/CD pipeline integration[65:30] Sample-driven development methodology and long-lived characterization tests[72:15] Production testing automation and shell interface utilization[78:40] Model-based development integration and requirements traceability[82:10] When not to use Zephyr: Arduino simplicity vs RTOS complexity trade-offsNotable Quotes"With Zephyr, porting a Bluetooth project from one chip architecture to another took an hour for an intern, compared to what would traditionally be months of effort." — Luka Mustafa"How many times have you written a logging subsystem? If the answer is more than zero, then it shouldn't be the case. Someone needs to write it once, and every three years someone needs to rewrite it with a better idea." — Luka Mustafa"The real benefit comes from doing things the Zephyr way in Zephyr, because then you are adopting all of the best practices of developing the code, using all of the subsystems to the maximum extent." — Luka Mustafa"You want to make sure your team is spending time on things that make money for you, not on writing logging, for example." — Luka MustafaZephyr Project - Linux Foundation-backed RTOS project providing comprehensive embedded development ecosystemTwister Testing Framework - Zephyr's built-in testing framework for unit tests, hardware-in-the-loop, and CI/CD integrationZbus Inter-Process Communication - Advanced event bus system for modular embedded development and component decouplingiirnas - Open-source examples of Zephyr best practices and CI/CD pipeline implementationsCarles Cufi's Talk - Detailed presentation on Nordic's strategic decision to support Zephyr RTOS You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/  

Key Topics[05:30] Cross-disciplinary mobbing with firmware and hardware engineers in IoT development[12:45] Addressing efficiency objections: Local vs global optimization in embedded teams[18:20] DevOps collaboration patterns and reducing friction between software and infrastructure teams[25:10] Selling mob programming to management: Building trust through continuous delivery[35:40] Dynamic team composition and the law of personal mobility in technical teams[42:15] Coordinating mob teams with waterfall processes and hardware gate systems[48:30] Automated firmware protocol documentation and testing infrastructureNotable Quotes"When you initially hear about mobbing, you think everybody's inactive, but there's a lot of excess thought capacity around programming that can happen - somebody can be thinking about refactorings while others are typing the solution." — Chris Lucian"If you're all there, that whole feedback loop can happen in 15 minutes as opposed to 15 days. It's like technical debt - you pay now or pay later, and if you pay later, it's going to be more expensive." — Austin Chadwick"We tend to have multiple releases a day all the way to production. Most mobs will deliver to production at least twice a day - four hours of work and then deliver to prod." — Chris LucianResources MentionedMob Mentality Show - Podcast dedicated to mob programming practices and extreme programming techniquesKent Beck's Test-Driven Development Book - Foundational resource for understanding true TDD practices in embedded developmentAmy Edmondson's Teaming Book - Framework for understanding high uncertainty and high interdependence scenarios in technical teamsLiminal Thinking - Mental framework for breaking through belief-based barriers in agile transformation You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/  

Key Topics[03:45] Hardware-software coupling challenges and decoupling strategies[08:20] Documentation overhead in safety-critical medical device development[12:15] Breaking down silos between electrical, mechanical, and software engineering teams[18:30] Hardware abstraction layers as database abstraction equivalents[22:10] Introduction to mob programming: all brilliant minds working together[28:45] Flow efficiency and eliminating handoffs in embedded product development[35:20] Optimal mob sizes and team organization strategies[42:15] Inverse Conway maneuver for architectural alignment[48:30] Getting started with mob programming in embedded teamsNotable Quotes"If you can run unit tests on your host and run your embedded code in a simulator on your PC, that's a pretty good indicator that you've successfully decoupled it from the hardware." — Jeff Gable"You need to understand that documentation is actually part of your product. It's not separate from your product made of curly brackets - it's one and the same thing." — Luca Ingianni"Typing is not the bottleneck. It's the problem solving. This is a method of problem solving together faster." — Chris Lucian"If you get the whole system in the room and in the same mob, things just start cranking. You're not waiting for anything because everyone you need is there." — Austin ChadwickFind the Mob Mentality Show at https://mobmentalityshow.podbean.com/ You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/  

From Prototype to Product: Navigating Hardware Manufacturing with Violet SuIn this episode of the Agile Embedded Podcast, Luca speaks with Violet Su, Business Development Manager at Seed Studio, about the challenges and opportunities in hardware manufacturing. The conversation explores the realities of hardware development, from initial prototyping to mass production. Violet emphasizes the importance of getting products into users' hands quickly to gather feedback, even if they're not perfect. She highlights common pitfalls for newcomers to hardware manufacturing, including underestimating costs, certification requirements, and supply chain complexities. The discussion also covers the growing influence of AI in hardware development and how emerging connectivity technologies are shaping the future of embedded systems.Key Topics[01:30] Introduction to Seed Studio and its focus on open source hardware and AI[03:15] Changes in hardware development landscape over the past decade[06:45] Common challenges for hardware startups and innovators[12:30] The importance of early feedback and iterative development[16:20] Success story: OpenUC2 microscopy project collaboration[23:40] Indicators of a successful hardware project[28:15] Insights from Embedded World 2024 conference[33:10] Future trends in hardware beyond AINotable Quotes"You might be able to design one and it really works when you have a sample or 10 samples, but when we talk about products, there are a lot of nuances that we really need to think about." — Violet Su"You can fail faster so that you can succeed faster. We couldn't make a perfect project and we shouldn't expect to make a perfect product." — Violet Su"When they give you the complaints early on, you will be very thankful, and they know you listened as well." — Violet Su"The projects that might take off either really solve the pain of some people, or get people excited because it's something new." — Violet Su"There's nothing better than getting customer complaints early on, so you don't get them later on." — Luca IngianniResources MentionedSeed Studio - Company providing open source hardware and AI solutionsOpenUC2 - Open source modular microscopy project mentioned as a success storyConnect With UsReach out to Violet Su at [email protected] to discuss potential hardware collaborations with Seed StudioVisit seedstudio.com to explore their range of AI hardware and customization servicesConnect with Violet Su on LinkedIn for updates on hardware manufacturing trends You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/  

Luca and Jeff dive into how AI tools can supercharge embedded development workflows. Luca shares his extensive hands-on experience, while Jeff brings a fresh perspective as someone just starting to incorporate these tools. They explore how AI can help with coding, testing, and debugging - while emphasizing that good software engineering judgment remains crucial. The conversation is particularly timely since AI tools are evolving rapidly, unlike their usually more "evergreen" podcast topics.A key insight they discuss is that while AI tools offer amazing productivity boosts (much like IDEs did), they're not replacing experienced developers anytime soon. However, they raise interesting questions about the future job market for junior developers. Their take? Modern developers should absolutely embrace AI tools, but use them thoughtfully - especially when learning.Key Timestamps and Topics:00:00:00 - Welcome and episode overview00:00:43 - Why this topic won't age well (but that's okay!)00:02:20 - Breaking down different AI coding tools00:08:00 - Deep dive into aider and workflow integration00:20:02 - Using AI for testing and test-driven development00:27:00 - AI-assisted architecture work and its limitations00:30:40 - How AI helps explore unfamiliar codebases00:33:30 - Debugging with AI - pros and cons00:38:50 - What this means for development jobs00:43:59 - Using AI to learn new frameworks/languages00:46:15 - Embedded Online Conference preview You can find Jeff at https://jeffgable.com.You can find Luca at https://luca.engineer.Want to join the agile Embedded Slack? Click hereAre you looking for embedded-focused trainings? Head to https://agileembedded.academy/Ryan Torvik and Luca have started the Embedded AI podcast, check it out at https://embeddedaipodcast.com/